Senior Applied Scientist, Amazon Alexa - Amazon

Description We are a part of Amazon Alexa organization where our mission is "delight customers through contextual and personalized proactive experiences that keep customers informed, engaged, and productive without cognitive burden". We are developing advanced systems to deliver engaging, intuitive, and adaptive content recommendations across all Amazon surfaces. We aim to facilitate seamless reasoning and customer experiences, surpassing the capabilities of previous machine learning models. We are looking for a passionate, talented, and resourceful Senior Applied Scientist in the field of Natural Language Processing (NLP), Large Language Model (LLM), Recommender Systems and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware personal assistant. A successful candidate will have strong machine learning background and a desire to push the envelope in one or more of the above areas. The ideal candidate would also enjoy operating in dynamic environments, be self-motivated to take on challenging problems to deliver big customer impact, shipping solutions via rapid experimentation and then iterating on user feedback and interactions. Key job responsibilities As a Senior Applied Scientist, you will leverage your technical expertise and experience to demonstrate leadership in tackling large complex problems, setting the direction and collaborating with applied scientists and engineers to develop novel algorithms and modeling techniques to enable timely, relevant and delightful recommendations and conversations. Your work will directly impact our customers in the form of products and services that make use of various machine learing, deep learning and language model technologies. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in the state of art. Basic Qualifications - PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field, or Master's degree - PhD, or Master's degree and 6+ years of applied research experience - 3+ years of building machine learning models for business application experience - Experience programming in Java, C++, Python or related language Preferred Qualifications - PhD in Electrical Engineering, Computer Sciences, or Mathematics with specialties in natural language processing, recommendation system, information retrieval or reinforcement learning - 4+ years experience in building machine learning and deep learning models for large scale customer facing product of features - Hands on experience with LLMs - Publications at peer-reviewed NLP/ML conferences (e.g. ACL, EMNLP, NAACL, NeurIPS, ICLR, ICML, AAAI) - Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field - Solid software development experience - Good written and spoken communication skills Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.